2010 IEEE International Conference on Communication Systems 2010
DOI: 10.1109/iccs.2010.5686105
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Power-source-aware backbone routing in wireless sensor networks

Abstract: Abstract-Due to the limited energy-source and mostly unattended nature of the wireless sensor networks, efficient use of energy has a critical importance on the lifetime of the applications accomplished by such networks. Although in most of the cases sensor nodes are battery-powered, there are application scenarios in which battery-and mains-powered nodes coexist. In this paper, we present an approach and algorithms based on this approach that increase the lifetime of wireless sensor networks in such heterogen… Show more

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Cited by 1 publication
(2 citation statements)
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“…As mentioned earlier, there are both centralized and localized algorithms for backbone construction, and with our approach presented here, both are possible. Several centralized algorithms is discussed in an earlier study [34], and we present a distributed algorithm in this paper. Our distributed algorithm is deterministic; if there is a connected backbone, the proposed approach is able to construct it, whereas in randomized algorithms backbone connectivity is highly affected by node density.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…As mentioned earlier, there are both centralized and localized algorithms for backbone construction, and with our approach presented here, both are possible. Several centralized algorithms is discussed in an earlier study [34], and we present a distributed algorithm in this paper. Our distributed algorithm is deterministic; if there is a connected backbone, the proposed approach is able to construct it, whereas in randomized algorithms backbone connectivity is highly affected by node density.…”
Section: Related Workmentioning
confidence: 99%
“…1 (e). Several centralized algorithms based on the proposed approach were discussed in [34] previously. In this paper we propose a distributed algorithm and it is described in detail next.…”
Section: Extract a Backbonementioning
confidence: 99%